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Catching that fleeting detail

Editorial Coordinator
Seema M Parihar
smparihar@gmail.com

Time is the most dynamic dimension that can no longer be ignored in geospatial applications. Neither can it stay as a separate set of data and tools outside the GIS workspace. At a time when efforts for generating high resolution data at quick intervals through special sensors are underway - the scope for advancement in temporal tools, technology and their acceptance in GI Science is immense. This article explores this inevitable dimension vis-à-vis GIS

All events happen within space and time. There exist infinite possibilities at the same time. There is past, present and future and the world operates through linear cause-effect relationship. So every time an event causes an effect, that effect becomes the cause of another effect. Viewed this way, things ought to happen one at a time with a unique timeline and the output needs to be unique every time. But it might not happen so in reality, the world is synchronistic. It’s coincidental, many things happening simultaneously. Infinite possibilities co-exist at the same time. Everything is happening all at once, and everything is correlated and instantly synchronised with everything else. This simultaneity can only happen through what is called infinite correlation. GIS has the ability to store and integrate infinite number of things happening at different times and correlate them with one another thereby providing a comprehensive understanding of the issue.

Temporal dimension cannot be ignored

For optimal decision making in geospatial environment (hydrology, ecology, health, demography, finance etc.), the restoration of past and present information is mandatory. Environments are changing (Figures.1 & 2). On one hand, geometry and attributes are dynamic and on the other, their pace of interaction too is dynamic. The impact of open and close system further decides the effect in different time frames. Certainly, the tools required in GIS enabled environment need to have fast and accurate updating possibilities. Broadly this may include:

• Storage, management and visualisation of temporal data in a spatial context;

• Multi-disciplinary data analyses and processing for various applications; and

• Maps and reports of time series statistics and properties

The study, Snow Accumulation and Snowmelt Monitoring in Greenland and Antarctica, which appeared in the recently published book Dynamic Planet (2007), highlights the existing tools and the need for more advance technology for temporal studies. A team of National Aeronautics and Space Administration (NASA) scientists found evidence showing extensive areas of snow melt in west Antarctica in January 2005 due to warm temperatures. This was detected with NASA's QuikScat satellite. Using data from QuikScat, they measured snowfall accumulation and melt in Antarctica and Greenland from July 1999 through July 2005.

Even the capabilities of sensors are being improved and extended as the temporal importance of climatic data is being recognised. NASA and the National Oceanic and Atmospheric Administration (NOAA) said the climate sensor will be returned to the National Polar-orbiting Operational Environmental Satellite System (NPOESS) programme scheduled for launch in 2009 to monitor the ozone layer. There are more such evidences in site in other regions too.

 

 

 

 

 

 

 

 

 
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